An introduction to explainable AI, and why we need it By Patrick Ferris
Neural networks (and all of their subtypes) are increasingly being used to build programs that can predict and classify in a myriad of different settings.
Examples include machine translation using recurrent neural networks, and image classification using a convolutional neural network. Research published by Google DeepMind has sparked interest in reinforcement learning.
All of these approaches have advanced many fields and produced usable models that can improve productivity and efficiency.... "
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